Appendix to final report WP3 Francesco Bogliacino, Virginia Maestri INTERMEDIATE WORK PACKAGE 3 APPENDIX JULY 2012 GROWING INEQUALITIES IMPACTS
July 2012 Francesco Bogliacino, Virginia Maestri, Amsterdam. Correspondence address: francesco.bogliacino@gmail.com General contact: gini@uva.nl Bibliograhic Information Bogliacino, F., Maestri, V., (2012). Appendix to final report WP3. AIAS, GINI Intermediate Work Package 3 Appendix. Information may be quoted provided the source is stated accurately and clearly. Reproduction for own/internal use is permitted. This paper can be downloaded from our website www.gini-research.org.
Appendix to final report WP3 Francesco Bogliacino Virginia Maestri GINI seventh framework programme Cooperation, theme 8 Socio-economic sciences and humanities SSH-2009-2.2.1 Social inequalities, their implications and policy options July 2012 Intermediate Work Package 3 Appendix
Francesco Bogliacino, Virginia Maestri Page 4
Intermediate Work Package 3 Report-Appendix Table of contents Drivers of Growing Inequalities APPENDIX A. STYLIZED FACTS ON THE EVOLUTION OF INEQUALITY FOR GINI PROJECT COUNTRIES...7 A.1 Inequality according to different data sources....7 A.2 Inequality according to different indicators....19 A.3. Different patterns of Inequality...26 A.4. Top Income Shares and their evolution...29 APPENDIX B. INTER-LINKAGES AMONG DIFFERENT SOURCES OF INEQUALITY...35 APPENDIX C. ESTIMATED COEFFICIENTS FROM MINCERIAN REGRESSIONS FOR WAGES...41 INFORMATION ON THE GINI PROJECT...53 Page 5
Francesco Bogliacino, Virginia Maestri Page 6
Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Appendix A. Stylized facts on the evolution of inequality for GINI Project countries A.1 Inequality according to different data sources. In the following series of graphs, we report the GINI for net disposable income using the OECD equivalence scale, but calculated from different data sources. The sources are OECD, LIS, RED, SWIID and Eurostat (ECHP and then EU-SILC). Figure A. 1 Australia.26.28.3.32.34 1980 1990 2000 2010 SWIID OECD LIS Page 7
Francesco Bogliacino, Virginia Maestri Figure A. 2 Austria.2.25.3.35.4 1980 1990 2000 2010 SWIID OECD EUSILC LIS ECHP Figure A. 3 Belgium.22.24.26.28.3 1980 1990 2000 2010 SWIID OECD EUSILC LIS ECHP Page 8
Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Figure A. 4 Canada.27.28.29.3.31.32 1970 1980 1990 2000 2010 SWIID OECD LIS RED Figure A. 5 Czech republic.2.22.24.26.28 1985 1990 1995 2000 2005 2010 SWIID OECD EUSILC LIS ECHP Page 9
Francesco Bogliacino, Virginia Maestri Figure A. 6 Denmark.2.22.24.26.28 1980 1990 2000 2010 SWIID OECD EUSILC LIS ECHP Figure A. 7 Finland.2.22.24.26.28 1970 1980 1990 2000 2010 SWIID OECD EUSILC LIS ECHP Page 10
Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Figure A. 8 France.24.26.28.3 1980 1990 2000 2010 SWIID OECD EUSILC LIS ECHP Figure A. 9 Germany.24.26.28.3.32 1970 1980 1990 2000 2010 SWIID OECD EUSILC LIS ECHP RED Page 11
Francesco Bogliacino, Virginia Maestri Figure A. 10 Greece.31.32.33.34.35 1980 1990 2000 2010 SWIID OECD EUSILC LIS ECHP Figure A. 11 Hungary.24.26.28.3.32.34 1990 1995 2000 2005 2010 SWIID OECD EUSILC LIS ECHP F Page 12
Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities igure A. 12 Ireland.29.3.31.32.33.34 1980 1990 2000 2010 SWIID OECD EUSILC LIS ECHP Figure A. 13 Italy.28.3.32.34.36 1980 1990 2000 2010 SWIID OECD EUSILC LIS ECHP RED Page 13
Francesco Bogliacino, Virginia Maestri Figure A. 14 Luxembourg.22.24.26.28.3 1980 1990 2000 2010 SWIID OECD EUSILC LIS ECHP Figure A. 15 Netherlands.22.24.26.28.3 1970 1980 1990 2000 2010 SWIID OECD EUSILC LIS ECHP CBS Page 14
Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Figure A. 16 Poland.26.28.3.32.34.36 1990 1995 2000 2005 2010 SWIID OECD EUSILC LIS ECHP Figure A. 17 Portugal.3.32.34.36.38 1990 1995 2000 2005 2010 SWIID ECHP OECD EUSILC Page 15
Francesco Bogliacino, Virginia Maestri Figure A. 18 Slovak Republic.15.2.25.3 1990 1995 2000 2005 2010 SWIID OECD LIS Eurostat Figure A. 19 Spain.25.3.35.4 1980 1990 2000 2010 SWIID OECD EUSILC LIS ECHP RED Page 16
Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Figure A. 20 Sweden.16.18.2.22.24.26 1970 1980 1990 2000 2010 SWIID OECD EUSILC LIS ECHP RED Figure A. 21 United Kingdom.25.3.35.4 1970 1980 1990 2000 2010 SWIID OECD EUSILC LIS ECHP RED Page 17
Francesco Bogliacino, Virginia Maestri Figure A. 22 United States.3.32.34.36.38.4 1970 1980 1990 2000 2010 SWIID OECD LIS RED Page 18
Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities A.2 Inequality according to different indicators. In the following set of graphs we show a set of indicators (Gini, Varlog, P90-50 and P50-10 ratios) for earnings. The datasource is RED. Figure A. 23 Canada: P-Ratios 2 2.5 3 3.5 Canada - p50/p10 & p90/p50 ratio p50/p10 p90/p50 1970 1980 1990 2000 2010 Figure A. 24 Canada. Var-Log and Gini Canada - Gini coeff. & var(log(w)).3.4.5.6.7.8 varlog Gini 1970 1980 1990 2000 2010 Page 19
Francesco Bogliacino, Virginia Maestri Figure A. 25 Great Britain: P-Ratios United Kingdom - p50/p10 & p90/p50 ratio 2 2.5 3 p50/p10 p90/p50 1980 1985 1990 1995 2000 2005 Figure A. 26 Great Britain: Var-Log and GINI United Kingdom - Gini coeff. & var(log(w)).3.4.5.6.7 varlog Gini 1980 1985 1990 1995 2000 2005 Page 20
Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Figure A. 27 Italy: P-Ratios Italy - p50/p10 & p90/p50 ratio 1.4 1.5 1.6 1.7 1.8 p90/p50 p50/p10 1985 1990 1995 2000 2005 Figure A. 28 Italy: Var-Log and Gini Italy - Gini coeff. & var(log(w)).1.15.2.25 Gini varlog 1985 1990 1995 2000 2005 Page 21
Francesco Bogliacino, Virginia Maestri Figure A. 29 Spain: P-Rations Spain - p50/p25 & p90/p50 ratio 1.4 1.6 1.8 2 2.2 p90/p50 p50/p25 1985 1990 1995 2000 Figure A. 30 Spain: Var-Log and GINI Spain - Gini coeff. & var(log(w)).2.4.6.8 1 varlog Gini 1985 1990 1995 2000 Page 22
Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Figure A. 31 Germany: P-Ratios 2 2.5 3 3.5 Germany - p50/p10 & p90/p50 ratio p50/p10 p90/p50 1985 1990 1995 2000 2005 d Figure A. 32 Germany: Var-Log and GINI 2 2.5 3 3.5 Germany - p50/p10 & p90/p50 ratio p50/p10 p90/p50 1985 1990 1995 2000 2005 d Page 23
Francesco Bogliacino, Virginia Maestri Figure A. 33 Sweden: P-Ratios p5010 0 100 200 300 400 Sweden- p50/p10 & p90/p50 ratio p90/p50 p50/p10 1980 1985 1990 1995 2000 2005 1.6 1.7 1.8 1.9 p9050 Figure A. 34 Sweden: Var-Log and Gini.2.4.6.8 1 1.2 Sweden - Gini coeff. & var(log(w)) varlog Gini 1980 1985 1990 1995 2000 2005 Page 24
Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Figure A. 35 US: P-Ratios USA - p50/p10 & p90/p50 ratio 2 2.5 3 3.5 p50/p10 p90/p50 1970 1980 1990 2000 2010 Figure A. 36 US: Var-Log and Gini USA - Gini coeff. & var(log(w)).2.4.6.8 varlog Gini 1970 1980 1990 2000 2010 Page 25
Francesco Bogliacino, Virginia Maestri A.3. Different patterns of Inequality Figure A. 37 Canada: Var-log of different series g g 0.2.4.6.8 1980 1985 1990 1995 2000 2005 Hourly wage (male) Earnings Disp. income Hours of work (male) Pre.-gov. income Figure A. 38 Germany: Var-log of different series.2.4.6.8 1 1985 1990 1995 2000 2005 Hourly wage (male) Earnings Hours of work (male) Disp. income Page 26
Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Figure A. 39 Sweden: Var-log of different series.2.4.6.8 1 1.2 1980 1985 1990 1995 2000 2005 Earnings Disp. income Figure A. 40 Italy: Var-log of different series 0.2.4.6 1970 1980 1990 2000 2010 Earnings Hours of work (male) Disp. Income Hourly wage (male) Consumption Page 27
Francesco Bogliacino, Virginia Maestri Figure A. 41 United Kingdom: Var-log of different series 0.2.4.6.8 1980 1985 1990 1995 2000 2005 Hourly wage (male) Earnings Hours of work (male) Consumption Figure A. 42 USA: Var-log of different series 0.2.4.6.8 1970 1980 1990 2000 2010 Hourly wage (male) Earnings Disp. income Hours of work (male) Pre.-gov. income Consumption Page 28
Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities A.4. Top Income Shares and their evolution The following table illustrates the income definition used for the calculation of top income shares in each country. Definitions are taken from the World Top Income Database. Table A. 1 Income definition for the top share COUNTRY INCOME DEFINITION AUSTRALIA Actual gross income; adjustment made to taxable income prior to 1957 CANADA Gross income, adjusted for the grossing up of dividend income DENMARK Gross taxable income FRANCE Gross income, net of employee social security contributions FINLAND 1920-1992: taxable income/1949-2003: gross income JAPAN Gross income (significant capital income base erosion after 1946) ITALY Gross income but excluding interest income PORTUGAL Gross income SPAIN Gross income SWEDEN Gross income including transfers UNITED KINGDOM Prior to 1975 income net of certain deductions; from 1975 total income UNITED STATES Gross income, adjusted for net income deductions Figure A. 43 Top 0.1% country group 1 absolute difference 1971-2004 0 1 2 3 4 5 FIN SWE AUS GBR USA JAP FRA 1.2 1.4 1.6 1.8 2 top 0,1% income share -1971 Page 29
Francesco Bogliacino, Virginia Maestri Figure A. 44 Top 0.1% country group 2 absolute difference 1971-2006 0 2 4 6 SWE AUS GBR USA FRA 1.2 1.4 1.6 1.8 2 top 0,1% income share - 1971 Figure A. 45 Top 0.1% country group 3 absolute difference 1982-2004.5 1 1.5 2 2.5 PRT.5 1 1.5 2 2.5 top 0,1% income share - 1982 ITA ESP CAN Page 30
Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Figure A. 46 Top 1% country group 1 USA absolute difference 1971-2004 0 2 4 6 8 AUS SWE GBR JAP FRA FIN 6 7 8 9 10 top 1% income share - 1971 Figure A. 47 Top 1% country group 2 absolute difference 1971-2006 0 2 4 6 8 10 SWE AUS GBR USA FRA 6 6.5 7 7.5 8 8.5 top 1% income share - 1971 Page 31
Francesco Bogliacino, Virginia Maestri Figure A. 48 Top 1% country group 3 absolute difference 1982-2004 0 1 2 3 4 5 DNK PRT ITA ESP CAN 4 5 6 7 8 top 1% income share - 1982 Figure A. 49 Top 5% country group 1 USA absolute difference 1971-2004 0 2 4 6 8 10 AUS SWE GBR JAP FRA FIN 18 20 22 24 26 top 5% income share - 1971 Page 32
Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Figure A. 50 Top 5% country group 2 absolute difference 1971-2006 0 5 10 15 AUS SWE GBR USA FRA 18 19 20 21 22 top 5% income share - 1971 Figure A. 51 Top 5% country group 3 absolute difference 1982-2004 0 5 10 15 DNK PRT ITA CAN ESP 14 16 18 20 22 top 5% income share - 1982 Page 33
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Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Appendix B. Inter-linkages among different sources of inequality There is a generalized impression that inequality is somehow related with problem such as poverty and the material deprivation. Our understanding of the relationship among these measures is rather limited. The same holds for the relationship between income and wealth inequality. In this section we limit ourselves to the presentation of the statistical correlation. We start by plotting the association between income and wealth inequality. Both measures are affected by some biases: 1) income inequality does not keep into account in-kind benefits and imputed rents; 2) wealth inequality does not keep into account public pensions and human capital stocks. OECD (2008) shows that the inclusion of the in kind benefits has a progressive effect, while the effect of the inclusion of the items mentioned sub 2) are difficult to estimate, especially given that the institutional differences affect the incentives to accumulate wealth. One possible way to arrive to a less biased estimate of both and, also, to a potential association between the two variables (wealth and income) is the use of income net-worth as discussed by Weisbrod and Hansen (1968): it consists of transforming the net worth into a constant flow of income, using both an interest rate and life expectancy to discount. Unfortunately no data are available. In the figures below we plot Gini of Wealth taken from OECD (2008) for a selection of countries against Gini of Income taken from LIS. Whenever the s of the survey do not match we correct for the trend of Income Gini using data from SWIID (Slot, 2009). Besides the US, which stands as a deeply unequal society; the evidence for Europe shows a negative correlation. In Chapter 3 we will provide also some analytical discussion of the possible causes. In the same Appendix B we also plot the main associations between a set of common indicators: a) GDP per capita measured in purchasing power parity; b) poverty rate, measured as the share of persons with less than 60% of median equivalized income; c) GINI index of disposable income; d) measures of material deprivation and severe material deprivation, expressed as having at most four (respectively three) items of a bundle of fundamental goods (for a detailed definition see Eurostat). The source for the data is Eurostat. GDP per capita is strongly and negatively associated with indicators of poverty and material deprivation, supporting the fundamental statement that growth is a necessary condition for poverty reduction. Inequality is positively associated with material deprivation, severe and not severe, and poverty. The association is weak for the first Page 35
Francesco Bogliacino, Virginia Maestri measure and strong for the poverty rate, but in both cases data tend to be clustered, suggesting the possibility of multiple equilibria, namely the potential coexistence of different distribution of incomes for a given growth rate. Figure B. 1 Income Inequality versus Wealth Inequality GINI of Wealth vs GINI of Income Income GINI (SWIID).2.25.3.35.4 ITA GBR FIN CAN GER USA USA SWE.6.7.8.9 Wealth GINI Source: GINI of Wealth is taken from OECD (2008), GINI of Income is taken SWIID data (Solt, 2009). Figure B. 2Gini of Wealth for selected countries in 2000. Source: UNU WIDER (2009) Page 36
Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Figure B. 3Gini of Wealth for selected countries in 2011. Source: Global Wealth Report Credit Suisse 2011 (Shorrocks et al., 2011). Figure B. 4 GDP per capita versus material deprivation for a selection of countries in 2005. Source: Eurostat GDP p.c. PPP 10 15 20 25 30 35 NLD DNK AUT SWE IRL GBR BEL GER FIN FRA ITA ESP PRTCZE GRC HUN SVK POL 10 20 30 40 50 Deprivation Page 37
Francesco Bogliacino, Virginia Maestri Figure B. 5 GDP per capita versus severe material deprivation for a selection of countries in 2005. Source: Eurostat GDP p.c. PPP 10 15 20 25 30 35 IRL NLD AUT SWE DNK GBR BEL FIN GER FRA ITA ESP PRT CZE GRC HUN SVK POL 0 10 20 30 40 Severe Deprivation Figure B. 6Gini versus material deprivation for a selection of countries in 2005. Source: Eurostat Gini.2.25.3.35.4 GBR ITA ESP IRL FRA BEL NLD AUT GER FIN DNK SWE PRT CZE GRC HUN SVK POL 10 20 30 40 50 Deprivation Page 38
Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Figure B. 7Gini versus severe material deprivation for a selection of countries in 2005. Source: Eurostat Gini.2.25.3.35.4 ESP FRA BEL NLD AUT FIN GER DNK SWE GBR ITA IRL PRT GRC CZE HUN SVK POL 0 10 20 30 40 Severe Deprivation Figure B. 8Gini versus poverty rate for a selection of countries in 2005. Source: Eurostat Gini.2.25.3.35.4 FRA NLD AUT FINGER CZE DNK SWE BEL GBR PRT ITA ESP IRL GRC HUN SVK POL 10 20 30 40 50 Poverty Rate Page 39
Francesco Bogliacino, Virginia Maestri Figure B. 9 GDP per capita versus poverty rate for a selection of countries in 2005. Source: Eurostat GDP p.c. PPP 10 15 20 25 30 35 NLD AUT SWE DNK FINGER FRA CZE IRL GBR BEL ITA ESP PRT GRC HUN SVK POL 10 20 30 40 50 Poverty Rate Page 40
Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Appendix C. Estimated coefficients from Mincerian regressions for wages Figure C. 1Australia: Estimated coefficients from a Mincerian regression. Source: LIS 0.2.4.6.8 1985 1990 1995 2000 2005 MAN/PROF TERTIARY Figure C. 2Australia: Estimated coefficients from a Mincerian regression. Source: LIS.2.3.4.5 1985 1990 1995 2000 2005 MANUF FINANCE Page 41
Francesco Bogliacino, Virginia Maestri Figure C. 3 Austria: Estimated coefficients from a Mincerian regression. Source: LIS 0.2.4.6 1996 1998 2000 2002 2004 MAN/PROF MANUF TERTIARY Figure C. 4 Belgium: Estimated coefficients from a Mincerian regression. Source: LIS.2.3.4.5.6 1990 1995 2000 MAN/PROF TERTIARY Page 42
Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Figure C. 5 Belgium: Estimated coefficients from a Mincerian regression. Source: LIS 0.1.2.3 1994 1996 1998 2000 2002 MANUF FINANCE Figure C. 6 Canada: Estimated coefficients from a Mincerian regression. Source: LIS.1.2.3.4.5 1985 1990 1995 2000 2005 MAN/PROF MANUF TERTIARY FINANCE Page 43
Francesco Bogliacino, Virginia Maestri Figure C. 7 Denmark: Estimated coefficients from a Mincerian regression. Source: LIS 0.2.4.6.8 1985 1990 1995 2000 2005 MAN/PROF MANUF TERTIARY FINANCE Figure C. 8 Finland: Estimated coefficients from a Mincerian regression. Source: LIS 0.5 1 1.5 2 1985 1990 1995 2000 2005 MAN/PROF MANUF TERTIARY FINANCE Page 44
Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Figure C. 9 France: Estimated coefficients from a Mincerian regression. Source: LIS.2.3.4.5.6 1990 1995 2000 2005 2010 MAN/PROF TERTIARY Figure C. 10 France: Estimated coefficients from a Mincerian regression. Source: LIS 0.2.4.6 1990 1995 2000 2005 2010 MANUF FINANCE Page 45
Francesco Bogliacino, Virginia Maestri Figure C. 11 Germany: Estimated coefficients from a Mincerian regression. Source: LIS 0.2.4.6.8 1 1980 1990 2000 2010 MAN/PROF MANUF TERTIARY FINANCE Figure C. 12 Hungary: Estimated coefficients from a Mincerian regression. Source: LIS.1.2.3.4.5.6 1990 1995 2000 2005 2010 MAN/PROF MANUF TERTIARY FINANCE Page 46
Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Figure C. 13 Ireland: Estimated coefficients from a Mincerian regression. Source: LIS 0.2.4.6.8 1990 1995 2000 2005 MAN/PROF MANUF TERTIARY FINANCE Figure C. 14 Italy: Estimated coefficients from a Mincerian regression. Source: LIS 0.2.4.6.8 1985 1990 1995 2000 2005 MAN/PROF MANUF TERTIARY FINANCE Page 47
Francesco Bogliacino, Virginia Maestri Figure C. 15 Luxembourg: Estimated coefficients from a Mincerian regression. Source: LIS 0.2.4.6.8 1 1990 1995 2000 2005 MAN/PROF MANUF TERTIARY FINANCE Figure C. 16 The Netherlands: Estimated coefficients from a Mincerian regression. Source: LIS -.2 0.2.4.6 1985 1990 1995 2000 2005 MAN/PROF MANUF TERTIARY FINANCE Page 48
Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Figure C. 17 Poland: Estimated coefficients from a Mincerian regression. Source: LIS -.2 0.2.4.6 1986 1988 1990 1992 1994 1996 MAN/PROF MANUF TERTIARY FINANCE Figure C. 18 Slovenia: Estimated coefficients from a Mincerian regression. Source: LIS -.2 0.2.4.6 1996 1998 2000 2002 2004 MAN/PROF MANUF TERTIARY FINANCE Page 49
Francesco Bogliacino, Virginia Maestri Figure C. 19 Spain: Estimated coefficients from a Mincerian regression. Source: LIS 0.2.4.6.8 1980 1985 1990 1995 2000 2005 MAN/PROF MANUF TERTIARY FINANCE Figure C. 20 United Kingdom: Estimated coefficients from a Mincerian regression. Source: LIS 0.2.4.6.8 1985 1990 1995 2000 2005 MAN/PROF FINANCE MANUF Page 50
Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Figure C. 21 USA: Estimated coefficients from a Mincerian regression. Source: LIS.65.7.75.8 1985 1990 1995 2000 2005 MAN/PROF TERTIARY Figure C. 22 USA: Estimated coefficients from a Mincerian regression. Source: LIS.2.3.4.5.6.7 1985 1990 1995 2000 2005 MANUF FINANCE Page 51
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Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Information on the GINI project Aims The core objective of GINI is to deliver important new answers to questions of great interest to European societies: What are the social, cultural and political impacts that increasing inequalities in income, wealth and education may have? For the answers, GINI combines an interdisciplinary analysis that draws on economics, sociology, political science and health studies, with improved methodologies, uniform measurement, wide country coverage, a clear policy dimension and broad dissemination. Methodologically, GINI aims to: exploit differences between and within 29 countries in inequality levels and trends for understanding the impacts and teasing out implications for policy and institutions, elaborate on the effects of both individual distributional positions and aggregate inequalities, and allow for feedback from impacts to inequality in a two-way causality approach. The project operates in a framework of policy-oriented debate and international comparisons across all EU countries (except Cyprus and Malta), the USA, Japan, Canada and Australia. Inequality Impacts and Analysis Social impacts of inequality include educational access and achievement, individual employment opportunities and labour market behaviour, household joblessness, living standards and deprivation, family and household formation/breakdown, housing and intergenerational social mobility, individual health and life expectancy, and social cohesion versus polarisation. Underlying long-term trends, the economic cycle and the current financial and economic crisis will be incorporated. Politico-cultural impacts investigated are: Do increasing income/educational inequalities widen cultural and political distances, alienating people from politics, globalisation and European integration? Do they affect individuals participation and general social trust? Is acceptance of inequality and policies of redistribution affected by inequality itself? What effects do political systems (coalitions/winner-takes-all) have? Finally, it focuses on costs and benefi ts of policies limiting income inequality and its effi ciency for mitigating other inequalities (health, housing, education and opportunity), and addresses the question what contributions policy making itself may have made to the growth of inequalities. Support and Activities The project receives EU research support to the amount of Euro 2.7 million. The work will result in four main reports and a final report, some 70 discussion papers and 29 country reports. The start of the project is 1 February 2010 for a three- period. Detailed information can be found on the website. www.gini-research.org Page 53
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